Unsharp masking is used in photography for highlighting edges of images. To this end, a blurred version of an image is subtracted from the original image to produce an unsharp image model. This mask is then superimposed on the original image to increase the contrast of any abrupt contrast transitions (i.e., edges) within the image. This process can be described by a linear equation: EQU I.sub.out =I.sub.in +C(I.sub.in -I.sub.mask)
where
I.sub.in =the original image PA1 I.sub.mask =the blurred image PA1 C=a sharpening control variable PA1 I.sub.out =the edge sharpened image
Digital images are composed of discrete tones (e.g., often only black and white pixels), so the perceived quality of these images strongly depends on the human visual response to the printed pixel patterns that define the images. Thus, continuous tone images are most effectively represented by pixel patterns, such as halftoned pixel patterns which are optimized to create the appearance of smooth, well controlled contrast variations, while line art images, such as text, are better represented by pixel patterns which are optimized to create the appearance of sharp, crisp contrast variations. Therefore, it would be beneficial to be able to dynamically tune a digital unsharp image mask to the type of digital image that is being printed so that edge highlighting of the unsharp mask can be realized without detracting from the perceived quality of digitally printed image as a whole.
Sometimes perceived image quality is secondary to the goal of printing the fundamental information contrast of the image at the lowest possible cost. Some printers have a "draft" printing mode for this purpose. The fundamental information contrast of many images is represented by the edges of the compositional elements of these images. Consequently, it would be beneficial to have a technique for generating effectively "differentiated" versions of digital images so that marking material (e.g., toner or ink) can be saved when printing these images in a "draft" mode.